文章摘要
郑英杰,赵耐青,何一宁.客观世界的因果关系:基于有向无环图的结构解析[J].中华流行病学杂志,2018,39(1):90-93
客观世界的因果关系:基于有向无环图的结构解析
Causality in objective world: Directed Acyclic Graphs-based structural parsing
收稿日期:2017-05-12  出版日期:2018-01-13
DOI:10.3760/cma.j.issn.0254-6450.2018.01.019
中文关键词: 因果关系;有向无环图;混杂;病因网络;时序关系
英文关键词: Causality;Directed Acyclic Graphs;Confounding;Causal Web;Temporality
基金项目:国家自然科学基金(81373065,81773490);上海市第四轮公共卫生体系建设三年行动计划重点学科项目(15GWZK0202)
作者单位E-mail
郑英杰 200032 上海, 复旦大学公共卫生学院卫生微生物学教研室 复旦大学公共卫生学院教育部公共卫生安全重点实验室 复旦大学卫生部卫生技术评估重点实验室 yjzheng@shmu.edu.cn 
赵耐青 200032 上海, 复旦大学公共卫生学院生物统计学教研室  
何一宁 200032 上海, 复旦大学公共卫生学院卫生微生物学教研室 复旦大学公共卫生学院教育部公共卫生安全重点实验室 复旦大学卫生部卫生技术评估重点实验室  
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中文摘要:
      客观世界因果关系的整体框架较为笼统而缺乏明晰的细节,给因果关系的研究带来困难。本文基于因果关系的时序特性结合有向无环图(DAGs),以因和果的发生时间为界,将客观世界的时间维度划分为3个时间域和2个时间点。通过对5个时间单位上变量间存在着的完整的因果关系的病因网络DAGs进行分析发现,其病因结构由两部分叠加组成:第一部分是各个时间域间/时间点上任取一变量间的组合DAGs,为因果关系的基本结构,构成病因网络的核心,仅混杂路径影响其因果效应估计;第二部分是各个时间域内/时间点上变量间的母子或祖先-后代关系,其DAGs表现为与混杂类似的结构。本文简洁明了地构建了客观世界因果关系研究的整体框架(病因网络DAGs),解释了控制混杂以解决因果效应估计的结构基础,为正确研究和识别因果关系奠定基础。
英文摘要:
      The overall details of causality frames in the objective world remain obscure, which poses difficulty for causality research. Based on the temporality of cause and effect, the objective world is divided into three time zones and two time points, in which the causal relationships of the variables are parsed by using Directed Acyclic Graphs (DAGs). Causal DAGs of the world (or causal web) is composed of two parts. One is basic or core to the whole DAGs, formed by the combination of any one variable originating from each time unit mentioned above. Cause effect is affected by the confounding only. The other is an internal DAGs within each time unit representing a parent-child or ancestor-descendant relationship, which exhibits a structure similar to the confounding. This paper summarizes the construction of causality frames for objective world research (causal DAGs), and clarify a structural basis for the control of the confounding in effect estimate.
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